AWS for Industries

Health eCareers: revolutionizing job searches with generative AI on AWS

In a rapidly evolving healthcare job market, finding the perfect role can be overwhelming. Health eCareers, a premier job board for healthcare professionals, is changing the game with a new AI-driven search experience.

This blog explores how Health eCareers built high-impact, production-ready AI workloads on Amazon Web Services (AWS) to make job hunting faster, smarter, and more intuitive.

The Challenge: overcoming complexity in Healthcare job searches

Traditional job search interfaces are often cluttered with checkboxes, dropdowns, and filters that can overwhelm job searchers. According to Health eCareers’ years of data, many users abandon job searches due to complex or inefficient filtering systems—resulting in frustration, missed opportunities, and prolonged hiring timelines.

This challenge highlighted the need for a more intuitive approach to match healthcare professionals with relevant job openings quickly and efficiently. Health eCareers saw an opportunity to improve the search process by allowing users to input queries in plain language. For example, “Show me surgical positions in Southern California for orthopedic surgeons.” This helps users reach highly relevant results with minimal effort. The goal was not only to enhance user engagement, but to drive higher application rates for positions by reducing search friction.

The Solution: Leveraging Amazon Bedrock for generative AI

Health eCareers needed a powerful, secure, and accurate solution capable of handling high volumes of personalized job search requests. They sought to simplify the job search process using advanced large language models (LLMs) that could understand complex medical job roles and user intent with minimal input, thereby making job searching as straightforward as having a conversation.

Amazon Bedrock emerged as the ideal choice, offering robust foundation models, including Anthropic Claude and Amazon Titan Text Embeddings. Both are optimized for complex language processing and effective semantic representation. By leveraging the diverse LLMs within Amazon Bedrock from both AWS and leading AI providers, Health eCareers was able to build an intuitive, AI-driven tool that transforms traditional job search into an engaging, conversational experience.

Here’s how the system works behind the scenes:

1. User Interaction: When a user enters a job query on the Health eCareers’ website, the input is processed through a .NET application using the Amazon Bedrock SDK on Amazon Elastic Container Service (Amazon ECS). The prompt is first sanitized and then passed to the Anthropic Claude foundational model hosted on Amazon Bedrock for further processing.

2. Geographical Understanding and Vectorization: The Anthropic Claude foundational model plays a crucial role in identifying and interpreting geographical references within the query. For instance, a term like “Boston area” is converted into geo-coordinates. Once the prompt is enhanced, it is sent to an Amazon Titan embedding model to be vectorized.

3. Semantic Search: The vectorized query is then sent to an Elasticsearch cluster hosted on an Amazon Elastic Compute Cloud (Amazon EC2) instance. This search engine performs a semantic search across the entire job posting vectorized repository (creating a Knowledge Base), which is updated every six hours.

4. Knowledge Base: The Job posting data is first stored in Amazon Simple Storage Service (Amazon S3) and then vectorized using Amazon Titan embedding before being stored as a vector in Elasticsearch.

5. Generative AI Response: The top relevant job postings returned by Elasticsearch are then combined with the original query and sent back to the Anthropic Claude foundational model through Amazon Bedrock. Here, a generative AI response is crafted, providing the user with a set of relevant job postings and a tailored answer to their query.

6. User Experience: The result is presented to the user in a seamless chat experience. Users can refine their search or dive deeper into the job details. This all makes the process interactive and efficient.

This image provides a high-level architectural overview of Health eCareers' generative AI-driven job search tool built on AWS. The architecture includes a user interaction layer where job queries are processed through an application. The system uses Amazon Bedrock to process queries, employing models like Anthropic Claude for h "geographical understanding processing and Amazon Titan for vectorization. An Elasticsearch cluster on Amazon EC2 performs a semantic search on vectorized job postings stored in Amazon S3. The results are returned to the user in an interactive chat experience, enhancing search relevancy and efficiency.

Figure 1: Overview of the Architecture (simplified)

For a deeper look into the technical architecture, Health eCareers showcased this solution on the This Is My Architecture video series on AWS. Watch the episode here to see how the components, such as Amazon ECS, Elasticsearch, and Amazon S3, work together to create a seamless job search experience powered by generative AI (Amazon Bedrock).

The Impact: A Smarter Job Search Tool

In just eight weeks, Health eCareers moved from concept to production with AWS, creating an AI-driven tool that has transformed job searches for healthcare professionals. With an over 80% application rate for jobs surfaced by the generative AI search, Health eCareers is seeing higher engagement, which directly benefits its business model. Since Health eCareers earns revenue from its healthcare partners and job providers, increased applications and relevant job matches directly contribute to its success by delivering higher value to its partners.

This improvement is significant compared to traditional search methods, where job seekers often struggled to find relevant roles, resulting in abandoned searches and fewer applications. By addressing these challenges, Health eCareers has achieved an 18% increase in usage of the generative AI-driven job search since its third quarter of 2024 and a 30% increase in job applications among AI tool users. These metrics not only demonstrate that users are finding more relevant jobs, but also indicate greater satisfaction with the platform and more demand from partners and job providers.

Furthermore, Health eCareers has expanded its AI capabilities with a Cover Letter Creator and a generative AI-powered “Am I a Good Fit for This Job?” feature. It helps job seekers build confidence and apply more efficiently.

Conclusion

Health eCareers has effectively harnessed generative AI to revolutionize the job search experience for healthcare professionals. By leveraging Amazon Bedrock (along with foundational models like Amazon Titan and Anthropic Claude) and additional AWS services (such as Amazon EC2 and Amazon ECS), Health eCareers has created a tool that simplifies the search process and delivers highly relevant results. This transformation is only the beginning, with future plans for personalized job recommendations and AI-driven career coaching.

Contact an AWS Representative to know how we can help accelerate your business.

Further Reading

Health eCareers

Health eCareers is the leading job board and career resource for healthcare professionals. Many Health eCareers employees have family and friends who are healthcare professionals. For almost 30 years, Health eCareers has served as the leading recruitment and career resource for healthcare providers. With thousands of healthcare employers and an exclusive network of premier healthcare associations across the United States, Health eCareers brings together physicians and advanced practice providers with employers looking for top talent.

Pedram Jahangiri

Pedram Jahangiri

Pedram Jahangiri is an Enterprise Solution Architect at AWS with a PhD in Computer and Electrical Engineering. With over 15 years of expertise in the Cloud, Operational Technology (OT), IT, AI/ML, and Energy industries, he has a solid history of leading technical teams and developing strategic initiatives at AWS. He is also a distinguished speaker and author, known for his contributions to cloud, energy, and AI/ML technologies.

Bill Breen

Bill Breen

Bill Breen serves as the SVP of Software Engineering & Product Development at Everyday Health Group and acts as the CTO for key brands, including Health eCareers, Prime, and MedPage Today. With extensive experience in leading technology teams, Bill specializes in delivering impactful solutions that drive business growth and enhance digital experiences.

Greg Chang

Greg Chang

Greg Chang is the Managing Director of Health eCareers, a division of Everyday Health Group, where he oversees all business operations. With 6+ years in this role, Greg drives strategic growth, partnerships, and innovation in healthcare recruitment. His leadership has strengthened Health eCareers' position as a top career resource for healthcare professionals.